Through web-based media services like Twitter and Facebook, a user of a network (e.g., a social network) is exposed to a vast amount of information from hundreds if not thousands of messages or other activities from different online sources including friends and merchants, culminating in a massive information overload. Individuals and organizations are increasingly unable to filter signal from noise efficiently, or at all, in the growing number of information streams with which they must interact on a daily basis.
Although there are traditional ways to analyze correlations among sets of data, they remain cumbersome and/or labor-intensive to unsophisticated general users and smaller companies. It is desirable to provide systems and methods which enable an integrated, user-friendly user experience with automated mechanisms that can reveal correlation between data streams to users in a clear and easily understandable way, so that the users can stay informed and responsive to current or new trends.